The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Intelligence Testing for Autonomous Vehicles: A New Approach
Abstract
In this paper, we study how to test the intelligence of an autonomous vehicle. Comprehensive testing is crucial to both vehicle manufactories and customers. Existing testing approaches can be categorized into two kinds: scenario-based testing and functionality-based testing. We first discuss the shortcomings of these two kinds of approaches, and then propose a new testing framework to combine the benefits of them. Based on the new semantic diagram definition for the intelligence of autonomous vehicles, we explain how to design a task for autonomous vehicle testing and how to evaluate test results. Experiments show that this new approach provides a quantitative way to test the intelligence of an autonomous vehicle.
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Citations
Cites
Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations
Fagnant, D. J., & Kockelman, K. (2015) · Transportation Research Part A: Policy and Practice · doi:10.1016/j.tra.2015.04.003 · Cited by 3,214
Stanley: The robot that won the DARPA Grand Challenge
Thrun, S., Montemerlo, M., Dahlkamp, H., Stavens, D., Aron, A., Diebel, J., Fong, P., Gale, J., Halpenny, M., Hoffmann, G., et al. (2006) · Journal of Field Robotics · doi:10.1002/rob.20147 · Cited by 2,237
Data-Driven Intelligent Transportation Systems: A Survey
Zhang, J., Wang, F.-Y., Wang, K., Lin, W.-H., Xu, X., & Chen, C. (2011) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2011.2158001 · Cited by 1,817
Self-citationReal-Time Motion Planning With Applications to Autonomous Urban Driving
Kuwata, Y., Karaman, S., Teo, J., Frazzoli, E., How, J. P., & Fiore, G. (2009) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2008.2012116 · Cited by 889
Wang, F.-Y. (2010) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2010.2060218 · Cited by 856
Self-citationThe Quest for Artificial Intelligence
Nilsson, N. J. (2009) · Cambridge University Press eBooks · doi:10.1017/cbo9780511819346 · Cited by 783
Handbook of Intelligent Vehicles
(2012) · Springer eBooks · doi:10.1007/978-0-85729-085-4 · Cited by 377
Autonomous driving in urban environments: approaches, lessons and challenges
Campbell, M., Egerstedt, M., How, J. P., & Murray, R. M. (2010) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2010.0110 · Cited by 353
The DARPA Urban Challenge: Autonomous Vehicles in City Traffic
(2009) · Springer Tracts in Advanced Robotics · doi:10.1007/978-3-642-03991-1 · Cited by 341
Glaser, S., Vanholme, B., Mammar, S., Gruyer, D., & Nouveliere, L. (2010) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2010.2046037 · Cited by 336
Cited by
Capturing Car-Following Behaviors by Deep Learning
Wang, X., Jiang, R., Li, L., Lin, Y., Zheng, X., & Wang, F.-Y. (2018) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2017.2706963 · Cited by 325
Self-citationTesting machine learning based systems: a systematic mapping
Riccio, V., Jahangirova, G., Stocco, A., Humbatova, N., Weiss, M., & Tonella, P. (2020) · Empirical Software Engineering · doi:10.1007/s10664-020-09881-0 · Cited by 251
Testing and quality validation for AI software–perspectives, issues, and practices
Tao, C., Gao, J., & Wang, T. (2019) · IEEE Access · doi:10.1109/access.2019.2937107 · Cited by 60
“The authors gave the definition and generation of intelligence test tasks for vehicles to combine the benefits of scenario-based testing and functionality-based testing approaches based on a semantic relation diagram for driving intelligence proposed in [9].”
Method
Metadata
- Authors
- Li, L., Huang, W.-L., Liu, Y., Zheng, N.-N., & Wang, F.-Y.
- Venue
- IEEE Transactions on Intelligent Vehicles
- Published
- 2016-06
- Volume
- 1
- Issue
- 2
- Pages
- 158-166
- ISSN
- 2379-8858 (ISSN-L)
- 2379-8904
- OpenAlex
- W2521921275
- Cited by
- 267
- References
- 29
- FWCI
- 16.24
- Type
- journal article
- Language
- en
- Open access
- closed
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- Li, L., Huang, W.-L., Liu, Y., Zheng, N.-N., & Wang, F.-Y. (2016). Intelligence Testing for Autonomous Vehicles: A New Approach. IEEE Transactions on Intelligent Vehicles. https://doi.org/10.1109/tiv.2016.2608003
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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